1. Field of the Invention
The present invention relates to fusion for automatic target recognition (ATR).
2. Description of Related Art
Various ATR systems have been designed to obtain accurate predictions from target recognition results based on imagery obtained by one or more sensors. Such systems generally attempt to predict a target type from a set of target types based on sensor data and/or fused data (e.g., data from multiple sensors and/or multiple looks).
To predict the target type from a set of target types, at least one image must be processed and data must be extracted. Depending on the system requirements and/or parameters, the data may include confidence values (e.g., a percentage, estimate or likelihood) and a corresponding pose for each of the confidence values.
These systems have utilized decision level, hypothesis level and feature level fusion in attempts to determine the best ATR evidence to be fused. Decision level fusion ATR systems determine the best ATR evidence over a range of azimuth angles for each look, but ignore consistency or relationship criteria between pose information. This and other fusion systems generally fuse ATR scores without regard to detailed pose information within the pose space uncertainty. Moreover, such systems fuse ATR scores after significant portions of the data is pruned by the individual ATR systems prior to fusion. These ATR systems may prune portions of the data for reasons of efficiency, or a specific ATR system may be unable to provide accurate predictive data without pruning the data. For example, the ATR system may be designed to combine specific portions of data, but not other portions of data, such that specific portions of data are required for that specific ATR system. The ATR system may also be designed such that data must be pruned prior to fusion if the data does not have sufficient information (e.g., points of data).